Energy Expenditure During Incline Walking – Benefits of Integrating a Barometer into Activity Monitors
American Journal of Sports Science
Volume 6, Issue 2, June 2018, Pages: 47-54
Received: Feb. 15, 2018;
Accepted: Mar. 14, 2018;
Published: Apr. 4, 2018
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Armbruster Manuel, Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany; Institute of Sports and Sports Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
Anastasopoulou Panagiota, Institute of Sports and Sports Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
Altmann Stefan, Institute of Sports and Sports Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
Ringhof Steffen, Institute of Sports and Sports Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
Neumann Rainer, Institute of Sports and Sports Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
Haertel Sascha, Institute of Sports and Sports Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
Woll Alexander, Institute of Sports and Sports Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
Objective: This study aimed to compare different methods to determine energy expenditure (EE) on incline walking. Approach: The methods tested were a conventional triaxial accelerometer (GT3X), a versatile system (SenseWear), both utilizing single regression models, and a device equipped with a triaxial accelerometer and an air pressure sensor (move II). Twenty-five healthy participants wore the activity monitors and a portable indirect calorimeter (IC) as reference while walking up- and downhill as well as up- and downstairs. The accuracy of the three devices for estimating EE was assessed based on Pearson correlation, ICC, and Bland–Altman analysis. Main results: For GT3X and SenseWear the ICCs showed a weak correlation (between 0.42 and 0.08) and for move II a strong correlation (between 0.97 and 0.84) between the prediction of energy cost and the output from IC, respectively. Overall, the differences absolute to the IC values were 11 to 35 (12 to 30) times higher for the GT3X (SenseWear) than for the move II devices. Significance: The study showed that a device equipped with an accelerometer and an air pressure sensor had higher accuracy in predicting EE during incline walking than a conventional accelerometer or a versatile system.
Energy Expenditure During Incline Walking – Benefits of Integrating a Barometer into Activity Monitors, American Journal of Sports Science.
Vol. 6, No. 2,
2018, pp. 47-54.
Sirard J. R., Pate R. R. Physical activity assessment in children and adolescents. Sports medicine (Auckland, N. Z.). 2001; 31(6): 439-454.
Falck R. S., McDonald S. M., Beets M. W., Brazendale K., Liu-Ambrose T. Measurement of physical activity in older adult interventions: a systematic review. British journal of sports medicine. 2016; 50(8): 464-470.
Sun F., Norman I. J., While A. E. Physical activity in older people: a systematic review. BMC public health. 2013; 13: 449.
Perrin O., Terrier P., Ladetto Q., Merminod B., Schutz Y. Improvement of walking speed prediction by accelerometry and altimetry, validated by satellite positioning. Medical & biological engineering & computing. 2000; 38(2): 164-168.
Campbell K. L., Crocker P. R., McKenzie D. C. Field evaluation of energy expenditure in women using Tritrac accelerometers. Medicine and science in sports and exercise. 2002; 34(10): 1667-1674.
Terrier P., Aminian K., Schutz Y. Can accelerometry accurately predict the energy cost of uphill/downhill walking? Ergonomics. 2001; 44(1): 48-62.
Wang J., Redmond S. J., Voleno M., Narayanan M. R., Wang N., Cerutti S., Lovell N. H. Energy expenditure estimation during normal ambulation using triaxial accelerometry and barometric pressure. Physiological measurement. 2012; 33(11): 1811-1830.
Jeran S., Steinbrecher A., Pischon T. Prediction of activity-related energy expenditure using accelerometer-derived physical activity under free-living conditions: a systematic review. International journal of obesity. 2016; 40(8): 1187-1197.
Daniel C. R., Battistella L. R. Validation of accelerometry for measuring energy expenditure: a systematic review. Acta Fisiatr. 2014; 21(2): 87-92.
Vernillo G., Savoldelli A., Pellegrini B., Schena F. Validity of the SenseWear Armband to assess energy expenditure in graded walking. Journal of physical activity & health. 2015; 12(2): 178-183.
Chen K. Y., Sun M. Improving energy expenditure estimation by using a triaxial accelerometer. Journal of applied physiology (Bethesda, Md.: 1985). 1997; 83(6): 2112-2122.
Crouter S. E., Churilla J. R., Bassett D. R., Jr. Estimating energy expenditure using accelerometers. European journal of applied physiology. 2006; 98(6): 601-612.
Hey S., Anastasopoulou P., Haaren B. Erfassung körperlicher Aktivität mittels Akzelerometrie – Möglichkeiten und Grenzen aus technischer Sicht. B & G. 2014; 30(2): 73-78.
Yang C. C., Hsu Y. L. A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors (Basel, Switzerland). 2010; 10(8): 7772-7788.
Yamazaki T., Gen-No H., Kamijo Y., Okazaki K., Masuki S., Nose H. A new device to estimate VO2 during incline walking by accelerometry and barometry. Medicine and science in sports and exercise. 2009; 41(12): 2213-2219.
Duncan G. E., Lester J., Migotsky S., Higgins L., Borriello G. Measuring slope to improve energy expenditure estimates during field-based activities. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme. 2013; 38(3): 352-356.
Anastasopoulou P., Tubic M., Schmidt S., Neumann R., Woll A., Hartel S. Validation and comparison of two methods to assess human energy expenditure during free-living activities. PloS one. 2014; 9(2): e90606.
World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA: the journal of the American Medical Association. 2013; 310(20): 2191-2194.
Hills A. P., Mokhtar N., Byrne N. M. Assessment of physical activity and energy expenditure: an overview of objective measures. Frontiers in nutrition. 2014; 1: 5.
Macfarlane D. J., Wong P. Validity, reliability and stability of the portable Cortex Metamax 3B gas analysis system. European journal of applied physiology. 2012; 112(7): 2539-2547.
Anastasopoulou P., Tansella M., Stumpp J., Shammas L., Hey S. Classification of human physical activity and energy expenditure estimation by accelerometry and barometry. Conference proceedings:... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2012; 2012: 6451-6454.
Sasaki J. E., John D., Freedson P. S. Validation and comparison of ActiGraph activity monitors. Journal of science and medicine in sport / Sports Medicine Australia. 2011; 14(5): 411-416.
WHO. Energy and protein requirements. Report of a joint FAO/WHO/UNU Expert Consultation. World Health Organization technical report series. 1985; 724: 1-206.
Henry C. J. Basal metabolic rate studies in humans: measurement and development of new equations. Public health nutrition. 2005; 8(7a): 1133-1152.
Hollmann W., Strüder H. K., Tagarakis C. V. Spiroergometrie: Kardiopulmonale Leistungsdiagnostik des Gesunden und Kranken, Stuttgart, Schattauer; 2006.